Great course, very informative, with lots of valuable information and examples. Prof. Caffo and his team did a very good job in my opinion. I've found very useful the course material shared on github.
Excellent course that is jam-packed with useful material! It is quite challenging and gives a thorough grounding in how to approach the process of selecting a linear regression model for a data set.
por Cesar L•
Great course. The content might be improved to be more clear. I feel that sometimes the instructor assumes we are familiar with some concepts we have not seen in previous courses. Also, some times he does a very good job explaining the WHY before the HOW, and some other times he does not. Very knowledgeable instructor.
por Kevin H•
Something was missing from this course. I cam away with an increased understanding of regression but I still feel like I struggle with many concepts and had to put in much more time than the recommended.
Still when I found the answer it was all still contained and maybe the material itself is just advanced.
por Jeremy J•
Like the way the Prof uses media. This is a very light touch on a very deep subject so it has to balance analytical work with the light "trust me and just do it" approach. The balance was mostly there although on a couple items I don't know that I had a good enough grip to know what I don't know.
por Wei W•
Brian did better job in this course to elaborate and demonstrate with examples. No doubt Brian is extremely knowledge about this subject. Once again, this and Statistical Inference courses are very challenging to truly completed with insightful understanding. That's why I take one star away.
por Vidya M S•
The concepts are well explained and precise. I think it depends on the individual to dive deeper into the topic by independent learning. Good data examples. Also following the suggested book of the author helps with some extra excercises. However , I feel extra practice questions would help .
por Linda W•
This course will give you a good basic foundation in regression models. However, do be prepared to do a good amount of work besides just viewing the videos. I would recommend at the very least to go through the exercises in the 'recommended textbook' to gain a better understanding.
por Kim K•
You will need to know the subject before taking this class in order to understand or be able to put in a large amount of time to learn. The book "Introduction to Statistical Learning" is an excellent supplement to the course. Rigorous and rewarding when you put the work in.
Regression models was almost just as difficult as statistical inference. Again, the swirls and exercises were of great help. The pace, as always, was quite fast, but in the end all the pieces fitted together. Congratulations on a job well done!
por Peter G•
First 3 weeks give very reasonable overview of the subject - topics of linear / polynomial / multivariate regression are covered quite well.
Week 4 is a bit sloppy and ad-hoc, comparing to first 3 weeks - GLMs are given poorly.
por Utkarsh Y•
It is a good course for learning regression model implementation in R. You may need to have a basic understanding of popular regression models like linear & logistic as the course doesn't cover mathematical aspects in detail
por Tim M•
The course is informative & well taught. I would have liked to spend more time on GLM models, such as logistic regression. The Swirl assignments seem a bit outdated method of learning code and a bit of a hassle.
por Jim M•
Content is excellent and in depth. Structure could be better to present materials in a more organized fashion, particularly on how all the concepts and tools relate, and complex results interpretation.
por Andrew W•
Great subject, was a bit frustrated with some of the material (seemed rushed and not well prepared). Great assignment, but too restrictive on the max number of pages allowed. Wasted a lot of time.
por Diego C•
Very good course. Though basic, it provides you with the first tools and knowledge. The forums aren't what they used to be it seems, but you can find almost any answer there from past courses.
por Andrew W•
Very good at presenting basic concepts. I highly reccomend saving the quiz questions as a good guide as to what you should know. I wish there were more material on generalized linear models.
por Arturo M K•
I was hoping to learn about PROBIT models. I know they are very similar to LOGIT ones, but still... the pace is a little bit too fast and I think it requires more time than what it says.
por Bill K•
This was a tough class covering a lot of material. The last week on logistic regression completely lost me. If you're new to stats like me you might want to take it more than once.
por Manny R•
Really Fun Course. There is a lot to learn in this topic and this could be studied for a lifetime. I feel like I could apply this to discover solutions for issues at work.
por Vlad V•
Good course, worth taking. It points out the importance of looking deeper into the world of regression models and creates right mindset and anchors for future development.
por Samirou T•
I appreciate coefficients interpretation and variance influence to choose among models.
Running code takes a few seconds, understanding the model's outputs is a much hard
por David J B•
Probably the most conceptually challenging and practically useful course in the JH data science certification series (so far... I have a few more courses to complete).
por Fernando L B d M•
This time the professor Brian Caffo was more helpfull, explained better the concepts, and sometimes repeated some of the most important information... Good course!
por Nora M•
Good course for basic regression. Would have enjoyed more time spent on properly interpreting results and how they are relevant to answering business questions.
por Roopak M•
Nice course that helps make your foundations in regression modelling strong. The complexity of the course project can be increased to a more difficult level.
This course is a practical introduction to the regression models. Materials and organization are great, however slides and presentations require some work.